Latest generation of ProFound AI Risk offers greater accuracy and ethnically inclusive precision screening
Technology provides critical, risk-adaptive solutions for clinicians facing complex screening challenges presented by the COVID-19 pandemic
NASHUA, N.H., Sept. 29, 2021 (GLOBE NEWSWIRE) -- iCAD, Inc. (NASDAQ: ICAD), a global medical technology leader providing innovative cancer detection and therapy solutions, today announced the launch of ProFound AI® Risk for digital breast tomosynthesis (DBT), or 3D mammography, as well as an updated version of PowerLook® Density Assessment. Both technologies offer improved accuracy and enhanced functionality compared to previous versions of the software.
ProFound AI Risk is the world’s first commercially available clinical decision support tool that provides an accurate1,2 short-term breast cancer risk estimation that is truly personalized for each woman, based only on a 2D or 3D mammogram. The latest generation of PowerLook Density Assessment is the world’s first and only multi-vendor deep learning automated breast density assessment algorithm using synthetic images generated from 3D mammography.1,3
“ProFound AI Risk and PowerLook Density Assessment have the potential to truly transform personalized breast cancer screening and risk stratification as we know it,” said Stacey Stevens, President of iCAD, inc. “We believe these technologies will lead to more appropriate utilization of supplemental imaging and biopsies, less anxiety for women, and decreased costs to the system overall. We believe these solutions will be increasingly relevant in the years ahead, as mammography begins to transition from what is primarily an age-based screening paradigm today to a more effective and efficient risk-adjusted screening paradigm.”
ProFound AI Risk
The latest generation of ProFound AI Risk offers the ability to calculate a short-term risk estimation for 3D mammography, with greater accuracy compared to both the previous version of the risk software based on 2D mammography and traditionally used risk models. The latest version of ProFound AI Risk offers expanded features, including:
The ability to calculate short-term (one-, two- or three-year) absolute risk based on either 2D or 3D mammography images.
The ability to factor in clinically relevant global screening guidelines and more than 15 country incidence and mortality reference tables, including ethnicities, for alignment with that country’s general population.
“Factoring in a woman’s racial and ethnic background adds another dimension of personalization that allows clinicians to stratify risk in a more inclusive way,” added Stevens. “Studies show African American women have an approximately 40% higher risk of dying from breast cancer, and they are disproportionately affected by more aggressive subtypes, such as triple-negative breast cancer and inflammatory breast cancer, compared to white women.4,5,6 The latest generation of ProFound AI Risk offers the potential to address these racial disparities and improve outcomes for women, including those who may have higher risks of developing cancers between screenings due to genetic predispositions.”
ProFound AI Risk utilizes breast complexity findings, automated breast density and age in order to calculate a woman’s short-term, absolute risk of breast cancer. All of this information is within a woman’s screening mammogram, making risk assessment simple. Results include the woman’s absolute breast cancer risk score and breast cancer risk category [low, general, moderate and high].
“The need for technology like this has never been greater. The COVID pandemic truly highlighted the absence of a practical solution to accurately determine an individual’s risk of developing breast cancer between screenings, as several medical societies recommended last year that women of ‘average risk’ postpone mammograms. The issue is, most women simply don’t know their risk,” added Stevens. “As clinicians and facilities recover from the impact of the pandemic this year, they are presented with unprecedented challenges, including a significant reduction in patient volume, loss of income, and a growing mammography backlog. This technology offers a viable solution for the challenges clinicians are facing today and offers a solution that will remain relevant for years to come.”
Regular, age-based mammography screening reduces breast cancer mortality by approximately 20%,7 but screening mammography can still miss 20 to 40% of breast cancers.8,9 Many of these cancers are diagnosed as interval breast cancers, defined as those that emerge after a normal mammogram but before the woman’s next scheduled screening. These tumors are often diagnosed at a later stage than cancers detected by screening, and are associated with an increased risk of breast cancer-specific mortality, compared with cancers detected by screening.10
Clinicians have traditionally considered risk factors such as family history as a way to assess women’s risks of developing breast cancer, but about 85% of breast cancers occur in women who have no family history of breast cancer.11
ProFound AI Risk was created from an exclusive relationship between iCAD and leading researchers at the Karolinska Institutet in Stockholm, Sweden, one of the world’s foremost medical research universities and the home of the Nobel Assembly, which selects the Nobel laureates in Physiology or Medicine. This partnership built upon a previous research agreement whereby researchers at the Karolinska Institutet developed a breast cancer risk prediction model using information identified in mammography images provided by iCAD’s AI solutions.
“This leading-edge algorithm was designed to provide physicians with crucial information about a woman’s short-term risk of being diagnosed with breast cancer, so that they may further personalize her screening and surveillance plan. This may include screening frequency adjustment, supplemental imaging, genetic testing and/or risk reduction strategies,” according to Per Hall, MD, Professor/Senior Physician, Karolinska Institutet. “Ultimately, the goal of this technology is to enhance efficiency for clinicians and improve outcomes for patients.”
PowerLook Density Assessment
iCAD also launched the latest version of PowerLook® Density Assessment software on the new PowerLook 10 platform. This leading-edge software enables clinicians to automate breast density assessment accurately and reliably,1 removing the challenges of subjectivity. It identifies the patient’s anatomy, segments the breast, then measures adipose and fibroglandular tissue and its dispersion to determine the density category in alignment with BI-RADS® 5th Edition lexicon. Its consistent scores bring confident density assessment and standardized stratification in density-based breast cancer screening and reporting.
“Radiologist visual density assessment has suboptimal intra- and inter- observer agreement due to its visual, subjective assessment.12 This inconsistent reporting causes confusion, impacts patient care and derails referring physician and patient confidence,” said Randy Hicks, M.D., co-owner and CEO of Regional Medical Imaging in Michigan. “With PowerLook Density Assessment software, clinicians can feel confident in their patients’ density assessment. This solution is easy to integrate and implement, and is the ideal choice for those seeking to accurately automate density assessment and harmonize the patient experience.”
Density is a measure used to personalize screening, especially in the U.S., as the American College of Radiology recommends that supplemental imaging should be considered for women with dense breasts. Breast density is one of the strongest and most prevalent breast cancer risk factors;13 nearly half of all women age 40 and older who get mammograms are found to have dense breasts.14 Currently, 38 U.S. states require some form of density reporting15 and the FDA has proposed requiring breast density reporting to both patients and referring health providers.16
“Early cancer detection has a tremendous impact on women, from treatment to outcomes. These technologies empower clincians with the latest tools to personalize screening like never before,” added Stevens. “The commercialization of these products is not only a significant milestone for iCAD, it’s a giant leap forward in individualized patient care.”
ProFound AI Risk and PowerLook Density Assessment are the latest updates to iCAD’s Breast Health Solutions suite, which also includes the Company’s leading-edge cancer detection software, ProFound AI®. In 2018, ProFound AI for DBT became the first artificial intelligence (AI) software application trained using deep learning technology on DBT images to be FDA cleared. It offers clinically proven time-savings benefits to radiologists, reducing reading time by 52.7 percent, while also improving radiologist sensitivity by 8 percent, and reducing false positives and unnecessary patient recall rates by 7.2 percent.17
About iCAD, Inc.
Headquartered in Nashua, NH, iCAD is a global medical technology leader providing innovative cancer detection and therapy solutions. For more information, visit www.icadmed.com.
Certain statements contained in this News Release constitute “forward-looking statements” within the meaning of the Private Securities Litigation Reform Act of 1995, including statements about the expected benefits of ProFound AI® Risk for digital breast tomosynthesis (DBT) and the updated version of PowerLook® Density Assessment, the benefits of the Company’s products, and future prospects for the Company’s technology platforms and products. Such forward-looking statements involve a number of known and unknown risks, uncertainties and other factors which may cause the actual results, performance or achievements of the Company to be materially different from any future results, performance or achievements expressed or implied by such forward-looking statements. Such factors include, but are not limited, to the Company’s ability to achieve business and strategic objectives, the willingness of patients to undergo mammography screening in light of risks of potential exposure to Covid-19, whether mammography screening will be treated as an essential procedure, whether ProFound AI will improve reading efficiency, improve specificity and sensitivity, reduce false positives and otherwise prove to be more beneficial for patients and clinicians, the impact of supply and manufacturing constraints or difficulties on our ability to fulfill our orders, uncertainty of future sales levels, to defend itself in litigation matters, protection of patents and other proprietary rights, product market acceptance, possible technological obsolescence of products, increased competition, government regulation, changes in Medicare or other reimbursement policies, risks relating to our existing and future debt obligations, competitive factors, the effects of a decline in the economy or markets served by the Company; and other risks detailed in the Company’s filings with the Securities and Exchange Commission. The words “believe,” “demonstrate,” “intend,” “expect,” “estimate,” “will,” “continue,” “anticipate,” “likely,” “seek,” and similar expressions identify forward-looking statements. Readers are cautioned not to place undue reliance on those forward-looking statements, which speak only as of the date the statement was made. The Company is under no obligation to provide any updates to any information contained in this release. For additional disclosure regarding these and other risks faced by iCAD, please see the disclosure contained in our public filings with the Securities and Exchange Commission, available on the Investors section of our website at http://www.icadmed.com and on the SEC’s website at http://www.sec.gov.
Jessica Burns, iCAD
Brian Ritchie, LifeSci Advisors
1 iCAD data on file.
2 Eriksson M, Czene K, Strand F, Zackrisson S, Lindholm P, Lång K, Förnvik D, Sartor H, Mavaddat N, Easton D, Hall P. Identification of Women at High Risk of Breast Cancer Who Need Supplemental Screening. Radiology. 2020 Nov;297(2):327-333. doi: 10.1148/radiol.2020201620. Epub 2020 Sep 8. PMID: 32897160.
3 Based on publicly available data as of September 2021. For GE and Hologic only. Uses 2D synthetic images.
4 Richardson LC, Henley SJ, Miller JW, Massetti G, Thomas CC. Patterns and Trends in Age-Specific Black-White Differences in Breast Cancer Incidence and Mortality – United States, 1999–2014. MMWR Morb Mortal Wkly Rep 2016;65:1093–1098. DOI: http://dx.doi.org/10.15585/mmwr.mm6540a1external icon.
5 Siddharth S, Sharma D. Racial Disparity and Triple-Negative Breast Cancer in African-American Women: A Multifaceted Affair between Obesity, Biology, and Socioeconomic Determinants. Cancers (Basel). 2018;10(12):514. Published 2018 Dec 14. doi:10.3390/cancers10120514
6 American Cancer Society. Inflammatory Breast Cancer. https://www.cancer.org/cancer/breast-cancer/about/types-of-breast-cancer/inflammatory-breast-cancer.html#:~:text=IBC%20tends%20to%20occur%20in,common%20types%20of%20breast%20cancer.
7 Marmot M, Altman G, Cameron A, et al. The benefits and harms of breast cancer screening: an independent review. Br J Cancer. 2013;108(11):2205-2240.
8 NIH National Cancer Institute. Mammograms Fact Sheet. Accessed via https://www.cancer.gov/types/breast/mammograms-fact-sheet.
9 Lauby-Secretan B, Scoccianti C, Loomis D et al.; Breast-cancer screening--viewpoint of the IARC Working Group; N Engl J Med. 2015 Jun 11;372(24):2353-8. doi: 10.1056/NEJMsr1504363.
10 Irvin VL, Zhang Z, Simon MS, et al. Comparison of Mortality Among Participants of Women's Health Initiative Trials With Screening-Detected Breast Cancers vs Interval Breast Cancers. JAMA Netw Open. 2020;3(6):e207227. Published 2020 Jun 1. doi:10.1001/jamanetworkopen.2020.7227
11 U.S. Breast Cancer Statistics. Breastcancer.org. Accessed via https://www.breastcancer.org/symptoms/understand_bc/statistics.
12 Sprague B, Conant E, Onega T et al. Variation in Mammographic Breast Density Assessments Among Radiologists in Clinical Practice: A Multicenter Observational Study. Ann Intern Med. 2016; 165(7):457-464. doi:10.7326/M15-2934.
13 Engmann NJ, Golmakani MK, Miglioretti DL, Sprague BL, Kerlikowske K, Breast Cancer Surveillance C. Population-Attributable Risk Proportion of Clinical Risk Factors for Breast Cancer. JAMA Oncology 2017; 3:1228-1236.
14 National Cancer Institute. Dense Breasts: Answers to Commonly Asked Questions. Accessed via https://www.cancer.gov/types/breast/breast-changes/dense-breasts.
15 State Legislation Map. DenseBreast-Info.org. Accessed via https://densebreast-info.org/legislative-information/state-legislation-map/
16 National Reporting Standard. DenseBreast-Info.org. Accessed via https://densebreast-info.org/legislative-information/national-reporting-standard/
17 Conant, E et al. Improving Accuracy and Efficiency with Concurrent Use of Artificial Intelligence for Digital Breast Tomosynthesis. Radiology: Artificial Intelligence. 2019;1(4). Accessed via https://pubs.rsna.org/doi/10.1148/ryai.2019180096